remove quantization_aware option in Mobilenetv2-quant config

model_zoo/official/cv/mobilenetv2_quant/README_CN.md

@@ -102,10 +102,10 @@ MobileNetV2总体网络架构如下：
 - 配置MobileNetV2-quant和ImageNet2012数据集。
 
   ```python
-  'class_num':1000         # 数据集类数
+  'num_classes':1000       # 数据集类数
   'batch_size':134         # 训练批次大小
-  'epoch_size':60         # Mobilenetv2-quant的训练轮次
-  'start epoch':200         # 非量化网络预训练轮次
+  'epoch_size':60          # Mobilenetv2-quant的训练轮次
+  'start_epoch':200        # 非量化网络预训练轮次
   'warmup_epochs':0        # 热身轮次
   'lr':0.3                 # 学习率
   'momentum':0.9           # 动量

model_zoo/official/cv/mobilenetv2_quant/Readme.md

@@ -92,10 +92,10 @@ Parameters for both training and evaluation can be set in config.py
 - config for MobileNetV2-quant, ImageNet2012 dataset
 
   ```python
-  'class_num': 1000         # the number of classes in the dataset
+  'num_classes': 1000       # the number of classes in the dataset
   'batch_size': 134         # training batch size
-  'epoch_size': 60         # training epochs of mobilenetv2-quant
-  'start epoch':200         # pretraining epochs of unquantative network
+  'epoch_size': 60          # training epochs of mobilenetv2-quant
+  'start_epoch':200         # pretraining epochs of unquantative network
   'warmup_epochs': 0        # number of warmup epochs
   'lr': 0.3                 #learning rate
   'momentum': 0.9           # momentum

model_zoo/official/cv/mobilenetv2_quant/src/config.py

@@ -24,7 +24,7 @@ config_ascend_quant = ed({
     "data_load_mode": "mindata",
     "epoch_size": 60,
     "start_epoch": 200,
-    "warmup_epochs": 1,
+    "warmup_epochs": 0,
     "lr": 0.3,
     "momentum": 0.9,
     "weight_decay": 4e-5,
@@ -34,7 +34,6 @@ config_ascend_quant = ed({
     "save_checkpoint_epochs": 1,
     "keep_checkpoint_max": 300,
     "save_checkpoint_path": "./checkpoint",
-    "quantization_aware": True,
 })
 
 config_gpu_quant = ed({
@@ -42,7 +41,7 @@ config_gpu_quant = ed({
     "batch_size": 134,
     "epoch_size": 60,
     "start_epoch": 200,
-    "warmup_epochs": 1,
+    "warmup_epochs": 0,
     "lr": 0.3,
     "momentum": 0.9,
     "weight_decay": 4e-5,

tests/st/quantization/mobilenetv2_quant/test_mobilenetv2_quant.py

@@ -50,7 +50,6 @@ config_ascend_quant = ed({
     "save_checkpoint_epochs": 1,
     "keep_checkpoint_max": 300,
     "save_checkpoint_path": "./checkpoint",
-    "quantization_aware": True,
 })
 
 dataset_path = "/home/workspace/mindspore_dataset/cifar-10-batches-bin/"